Dograh is an open-source, self-hostable voice AI platform for building, deploying, and monitoring voice agents. It provides a visual workflow builder (node-based graph editor) for designing call flows, with deep integration across telephony providers (Twilio, Plivo, Vonage, Telnyx, Cloudonix, Vobiz, Asterisk ARI), STT/TTS/LLM models (OpenAI, Deepgram, Google, Azure, Cartesia, ElevenLabs, etc.), and real-time audio pipelines via the Pipecat library. The backend is a FastAPI monolith with PostgreSQL, Redis, and object storage, complemented by separate worker services (ARQ for background tasks) and a campaign orchestrator for bulk outbound calling. The system supports multi-tenancy, call recording, knowledge base/RAG, QA analysis, embeddable chat widgets, and an MCP server for AI-assisted workflow management. SDKs for Python and TypeScript enable programmatic workflow creation and outbound call triggering. While the core is a full-stack application, it includes evaluation frameworks for STT providers and post-call QA analysis, giving it a hybrid character but dominated by production application concerns.
ComfyUI-VoxCPM is a ComfyUI custom node package that provides expressive text-to-speech (TTS) using the VoxCPM model family (v1.x and v2). It supports zero-shot TTS, voice cloning (prompt or reference audio), voice design via text descriptions, LoRA inference, and LoRA fine-tuning. The architecture is a ComfyUI extension with heavy JavaScript frontend, HTTP API routes, and vendored model inference code. The core functionality is implemented in the `src/voxcpm/` directory, which contains model architectures (MiniCPM4, AudioVAE, local DiT, etc.), a standalone CLI, and training utilities. External dependencies include ComfyUI, PyTorch, Hugging Face Hub, and several optional libraries (argbind, datasets, modelscope, etc.). The codebase demonstrates good software engineering practices with clean abstractions, reusable components, and graceful degradation for optional features. However, it is tightly coupled to ComfyUI's ecosystem and vendors upstream model code, which may drift from upstream. The repository also includes a standalone `hf_progress` library for HuggingFace transfer progress tracking, which is a well-isolated, reusable component.